Name
Title | ||
|---|---|---|
A Study on Urban Traffic Congestion Dynamic Predict Method Based on Advanced Fuzzy Clustering Model |
Abstract | ||
|---|---|---|
With the rapid development of the increasing urban traffic demand, the road traffic congestion problems become serious matter. Traffic congestion not only increases the time of travel delay, but also wastes a lot of money. This paper introduces an urban traffic congestion dynamic predict method based on advanced fuzzy cluserting model. Moreover, the paper puts forward the warning measures based on above relative research results.Finally, the fuzzy cluster analysis methods are used to analyze 6 groups of the relevant parameters of traffic jams, classify and rank the traffic jams. The feasibility and effectiveness of that method which is presented in this paper are demonstrated by an example. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CIS.2008.194 | CIS |
Keywords | Field | DocType |
predictive models,security,transportation,fuzzy set theory,artificial neural networks,indexes | Traffic optimization,Fuzzy clustering,Mathematical optimization,Traffic flow,Computer science,Fuzzy logic,Computer network,Operations research,Fuzzy set,Traffic congestion reconstruction with Kerner's three-phase theory,Network traffic control,Traffic congestion | Conference |
Volume | Issue | ISSN |
2 | null | null |
ISBN | Citations | PageRank |
978-0-7695-3508-1 | 2 | 0.43 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhu Yin | 1 | 2 | 0.43 |
| Lu U. Huapu | 2 | 2 | 0.43 |
| Huapu Lu | 3 | 34 | 7.46 |